engleski

Link between orthogonal and standard multiple linear regression models

Several topics in connection with a recently proposed method for the orthogonalization of predictor variables (dominant component analysis) are considered. Applying the sequential regression procedure, it is shown that dominant component analysis and the standard multiple linear regression method are directly related to each other. In addition, it is demonstrated that an earlier proposed iterative procedure for the orthogonalization of a correlated variable can be efficiently replaced by one step regression. It is also shown that the coefficient of determination for an orthogonal descriptor coincides with the corresponding squared semipartial correlation coefficient. Finally, the origin of extra information in an orthogonalized predictor variable is discussed.

multiple linear regression ; dominant component method ; orthogonalization

nije evidentirano